Intake of sweet food, beverages and added sugars has been linked with depressive symptoms in several populations. Aim of this study was to investigate systematically cross-sectional and prospective ...associations between sweet food/beverage intake, common mental disorder (CMD) and depression and to examine the role of reverse causation (influence of mood on intake) as potential explanation for the observed linkage. We analysed repeated measures (23,245 person-observations) from the Whitehall II study using random effects regression. Diet was assessed using food frequency questionnaires, mood using validated questionnaires. Cross-sectional analyses showed positive associations. In prospective analyses, men in the highest tertile of sugar intake from sweet food/beverages had a 23% increased odds of incident CMD after 5 years (95% CI: 1.02, 1.48) independent of health behaviours, socio-demographic and diet-related factors, adiposity and other diseases. The odds of recurrent depression were increased in the highest tertile for both sexes, but not statistically significant when diet-related factors were included in the model (OR 1.47; 95% CI: 0.98, 2.22). Neither CMD nor depression predicted intake changes. Our research confirms an adverse effect of sugar intake from sweet food/beverage on long-term psychological health and suggests that lower intake of sugar may be associated with better psychological health.
Genetic variation helps to explain why some are susceptible, and others resistant, to the modern obesogenic world. Decades of twin and family studies have established that human body weight is highly ...heritable and it is as heritable now as it was prior to the obesity epidemic. Diminished physical activity levels, the modern food environment is deemed largely responsible for increases in obesity. However, despite the ubiquity of the (obesogenic) environment, we have not uniformly developed obesity. The sudden onset of the obesity epidemic in high-income countries at the end of the last century coincided with major changes to the food supply, resulting in larger portion sizes, greater availability and affordability of energy dense foods, and increased marketing. Recently, researchers from behavioral science, epidemiology, and genetics joined forces to propose that genetic risk of obesity likely operates via the neurobiology controlling appetite regulation. The working hypothesis is that genetic susceptibility to obesity manifests itself as the tendency to overeat when prompted by environmental food cues and the opportunity to eat.
The Child Eating Behaviour Questionnaire (CEBQ) is a validated parent-report measure of appetitive traits associated with weight in childhood. There is currently no matched measure for use in adults. ...The aim of this study was to adapt the CEBQ into a self-report Adult Eating Behaviour Questionnaire (AEBQ) to explore whether the associations between appetitive traits and BMI observed in children are present in adults. Two adult samples were recruited one year apart from an online survey panel in 2013 (n = 708) and 2014 (n = 954). Both samples completed the AEBQ and self-reported their weight and height. Principal component analysis (PCA) was used to derive 35 items for the AEBQ in Sample 1 and confirmatory factor analysis (CFA) was used to replicate the factor structure in Sample 2. Reliability of the AEBQ was assessed using Cronbach’s α and a two week test-retest in a sub-sample of 93 participants. Correlations between appetitive traits measured by the AEBQ and BMI were calculated. PCA and CFA results showed the AEBQ to be a reliable questionnaire (Cronbach’s α > 0.70) measuring 8 appetitive traits similar to the CEBQ Hunger (H), Food Responsiveness (FR), Emotional Over-Eating (EOE), Enjoyment of Food (EF), Satiety Responsiveness (SR), Emotional Under-eating (EUE), Food Fussiness (FF) and Slowness in Eating (SE). Associations with BMI showed FR, EF (p < 0.05) and EOE (p < 0.01) were positively associated and SR, EUE and SE (p < 0.01) were negatively associated. Overall, the AEBQ appears to be a reliable measure of appetitive traits in adults which translates well from the validated child measure. Adults with a higher BMI had higher scores for ‘food approach’ traits (FR, EOE and EF) and lower scores for ‘food avoidance’ traits (SR, EUE and SE).
The early obesogenic home environment is consistently identified as a key influence on child weight trajectories, but little research has examined the mechanisms of that influence. Such research is ...essential for the effective prevention and treatment of overweight and obesity.
To test behavioral susceptibility theory's hypothesis that the heritability of body mass index (BMI) is higher among children who live in more obesogenic home environments.
This study was a gene-environment interaction twin study that used cross-sectional data from 925 families (1850 twins) in the Gemini cohort (a population-based prospective cohort of twins born in England and Wales between March and December 2007). Data were analyzed from July to October 2013 and in June 2018.
Parents completed the Home Environment Interview, a comprehensive measure of the obesogenic home environment in early childhood. Three standardized composite scores were created to capture food, physical activity, and media-related influences in the home; these were summed to create an overall obesogenic risk score. The 4 composite scores were split on the mean, reflecting higher-risk and lower-risk home environments.
Quantitative genetic model fitting was used to estimate heritability of age-adjusted and sex-adjusted BMI (BMI SD score, estimated using British 1990 growth reference data) for children living in lower-risk and higher-risk home environments.
Among 1850 twins (915 49.5% male and 935 50.5% female; mean SD age, 4.1 0.4 years), the heritability of BMI SD score was significantly higher among children living in overall higher-risk home environments (86%; 95% CI, 68%-89%) compared with those living in overall lower-risk home environments (39%; 95% CI, 21%-57%). The findings were similar when examining the heritability of BMI in the separate food and physical activity environment domains.
These findings support the hypothesis that obesity-related genes are more strongly associated with BMI in more obesogenic home environments. Modifying the early home environment to prevent weight gain may be particularly important for children genetically at risk for obesity.
Emotional overeating (EOE) has been associated with increased obesity risk, while emotional undereating (EUE) may be protective. Interestingly, EOE and EUE tend to correlate positively, but it is ...unclear whether they reflect different aspects of the same underlying trait, or are distinct behaviours with different aetiologies. Data were from 2054 five-year-old children from the Gemini twin birth cohort, including parental ratings of child EOE and EUE using the Child Eating Behaviour Questionnaire. Genetic and environmental influences on variation and covariation in EUE and EOE were established using a bivariate Twin Model. Variation in both behaviours was largely explained by aspects of the environment completely shared by twin pairs (EOE: C = 90%, 95% CI: 89%-92%; EUE: C = 91%, 95% CI: 90%-92%). Genetic influence was low (EOE: A = 7%, 95% CI: 6%-9%; EUE: A = 7%, 95% CI: 6%-9%). EOE and EUE correlated positively (r = 0.43, p < 0.001), and this association was explained by common shared environmental influences (BivC = 45%, 95% CI: 40%-50%). Many of the shared environmental influences underlying EUE and EOE were the same (r
= 0.50, 95% CI: 0.44, 0.55). Childhood EOE and EUE are etiologically distinct. The tendency to eat more or less in response to emotion is learned rather than inherited.
The parental feeding practices (PFPs) of excessive restriction of food intake ('restriction') and pressure to increase food consumption ('pressure') have been argued to causally influence child ...weight in opposite directions (high restriction causing overweight; high pressure causing underweight). However child weight could also 'elicit' PFPs. A novel approach is to investigate gene-environment correlation between child genetic influences on BMI and PFPs. Genome-wide polygenic scores (GPS) combining BMI-associated variants were created for 10,346 children (including 3,320 DZ twin pairs) from the Twins Early Development Study using results from an independent genome-wide association study meta-analysis. Parental 'restriction' and 'pressure' were assessed using the Child Feeding Questionnaire. Child BMI standard deviation scores (BMI-SDS) were calculated from children's height and weight at age 10. Linear regression and fixed family effect models were used to test between- (n = 4,445 individuals) and within-family (n = 2,164 DZ pairs) associations between the GPS and PFPs. In addition, we performed multivariate twin analyses (n = 4,375 twin pairs) to estimate the heritabilities of PFPs and the genetic correlations between BMI-SDS and PFPs. The GPS was correlated with BMI-SDS (β = 0.20, p = 2.41x10-38). Consistent with the gene-environment correlation hypothesis, child BMI GPS was positively associated with 'restriction' (β = 0.05, p = 4.19x10-4), and negatively associated with 'pressure' (β = -0.08, p = 2.70x10-7). These results remained consistent after controlling for parental BMI, and after controlling for overall family contributions (within-family analyses). Heritabilities for 'restriction' (43% 40-47%) and 'pressure' (54% 50-59%) were moderate-to-high. Twin-based genetic correlations were moderate and positive between BMI-SDS and 'restriction' (rA = 0.28 0.23-0.32), and substantial and negative between BMI-SDS and 'pressure' (rA = -0.48 -0.52 - -0.44. Results suggest that the degree to which parents limit or encourage children's food intake is partly influenced by children's genetic predispositions to higher or lower BMI. These findings point to an evocative gene-environment correlation in which heritable characteristics in the child elicit parental feeding behaviour.
Extensive research has demonstrated the role of the Home Environment (HE) in shaping children's energy balance behaviours. Less is known about direct relationships with bodyweight. This review ...examines associations between the social and physical aspects of three pre-defined Home Environment domains (food, physical activity and media) and adiposity measures in children ≤12 years.
Six electronic databases (PubMed, Medline, EBSCO CINAHL, EMBASE, Web of Science, PsycInfo) were systematically searched up to October 2020. Studies reporting at least one physical and/or social aspect of the food, physical activity and/or media domains of the Home Environment in relation to child adiposity outcomes were included (n = 62).
Most studies examined one (n = 41) or two domains (n = 16). Only five studies assessed all three domains of the Home Environment. Most consistent relationships were observed for physical aspects of the home media environment; with greater availability of electronic devices associated with higher child adiposity (21/29 studies). Findings were less consistent for the smaller number of studies examining physical aspects of the home food or physical activity environments. 8/15 studies examining physical food environments reported null associations with adiposity. Findings were similarly mixed for physical activity environments; with 4/7 reporting null associations, 2/7 reporting negative associations and 1/7 reporting positive associations between access to physical activity equipment/garden space and adiposity. Fewer studies assessed social aspects (e.g. caregiver modelling or limit setting) of the Home Environment in relation to child adiposity and findings were again mixed; 9/16 media environment, 7/11 food environment and 9/13 physical activity environment studies reported null associations with child adiposity outcomes.
The home media environment was most consistently associated with adiposity in childhood. Findings were less consistent for the home food and physical activity environments. Greater agreement on definitions and the measurement of the obesogenic home environment is required in order to clarify the strength and direction of relationships with child adiposity. Robust longitudinal research using comprehensive measures of the holistic home environment is needed to better identify which aspects contribute to excess weight gain in childhood.
PROSPERO Systematic review registration number: CRD42018115139 .
Background
‘Food fussiness’ (FF) is the tendency to be highly selective about which foods one is willing to eat, and emerges in early childhood; ‘food neophobia’ (FN) is a closely related ...characteristic but specifically refers to rejection of unfamiliar food. These behaviors are associated, but the extent to which their etiological architecture overlaps is unknown. The objective of this study was to quantify the relative contribution of genetic and environmental influences to variation in FF and FN in early childhood; and to establish the extent to which they share common genetic and environmental influences.
Method
Participants were 1,921 families with 16‐month‐old twins from the Gemini birth cohort. Parents completed the Child Eating Behaviour Questionnaire which included three FF items and four FN items. Bivariate quantitative genetic modeling was used to quantify: (a) genetic and environmental contributions to variation in FF and FN; and (b) the extent to which genetic or environmental influences on FF and FN are shared across the traits.
Results
Food fussiness and FN were strongly correlated (r = .72, p < .001). Proportions of variation in FF were equally explained by genetic (.46; 95% CI: 0.41–0.52) and shared environmental influences (.46; 95% CI: 0.41–0.51). Shared environmental effects accounted for a significantly lower proportion of variation in FN (.22; 95% CI: 0.14–0.30), but genetic influences were not significantly different from those on FF (.58, 95% CI: 0.50–0.67). FF and FN largely shared a common etiology, indicated by high genetic (.73; 95% CI: 0.67–0.78) and shared environmental correlations (.78; 95% CI: 0.69–0.86) across the two traits.
Conclusions
Food fussiness and FN both show considerable heritability at 16 months but shared environmental factors, for example the home environment, influenced more interindividual differences in the expression of FF than in FN. FF and FN largely share a common etiology.
Mexico has one of the highest rates of obesity and overweight worldwide, affecting 75% of the population. The country has experienced a dietary and food retail transition involving increased ...availability of high-calorie-dense foods and beverages. This study aimed to assess the relationship between the retail food environment and body mass index (BMI) in Mexico.
Geographical and food outlet data were obtained from official statistics; anthropometric measurements and socioeconomic characteristics of adult participants (N = 22,219) came from the nationally representative 2012 National Health and Nutrition Survey (ENSANUT). Densities (store count/census tract area (CTA)) of convenience stores, restaurants, fast-food restaurants, supermarkets and fruit and vegetable stores were calculated. The association of retail food environment variables, sociodemographic data and BMI was tested using multilevel linear regression models.
Convenience store density was high (mean (SD) = 50.0 (36.9)/CTA) compared with other food outlets in Mexico. A unit increase in density of convenience stores was associated with a 0.003 kg/m
(95% CI: 0.0006, 0.005, p = 0.011) increase in BMI, equivalent to 0.34 kg extra weight for an adult 1.60 m tall for every additional 10% store density increase (number of convenience stores per CTA (km
)). Metropolitan areas showed the highest density of food outlet concentration and the highest associations with BMI (β = 0.01, 95% CI: 0.004-0.01, p < 0.001). A 10% store density increase in these areas would represent a 1 kg increase in weight for an adult 1.60 m tall.
Convenience store density was associated with higher mean BMI in Mexican adults. An excessive convenience store availability, that offers unhealthy food options, coupled with low access to healthy food resources or stores retailing healthy food, including fruits and vegetables, may increase the risk of higher BMI. This is the first study to assess the association of the retail food environment and BMI at a national level in Mexico.
Understanding the mechanisms through which deprivation predisposes a child to increased obesity risk is key to tackling health inequality. Appetite avidity is a key driver of variation in early ...weight gain. Low socioeconomic status (SES) can be a marker of a more ‘obesogenic’ food environment which may encourage the behavioural expression of appetite avidity. The objective was to test the hypothesis that children of lower SES demonstrate increases in appetite avidity from toddlerhood to five years. Data were from the Gemini twin birth cohort, with one twin per family selected at random. Parents completed the Child Eating Behaviour Questionnaire (CEBQ) to assess appetitive traits at 16 months and five years. SES was defined using a weighted composite measure comprising seven key correlates. Linear regression models examined the cross-sectional and prospective associations between SES and appetite from 16 months to 5 years, controlling for appetite at 16 months, sex, birth weight and parental BMI. Cross-sectionally, lower SES was significantly associated with higher food responsiveness (β = −0.09 ± 0.024), higher enjoyment of food (β = −0.13 ± 0.024), lower satiety responsiveness (β = 0.09 ± 0.024), and lower food fussiness (β = 0.09, ±0.024) at 16 months. At age 5, lower SES was significantly associated with higher food responsiveness (β = −0.10 ± 0.032), higher desire to drink (β = −0.22 ± 0.031) and higher emotional overeating (β = −0.10 ± 0.032). Prospectively, lower SES predicted greater increases in two key weight-related appetitive traits, from 16 months to 5 years: emotional overeating (β = −0.10 ± 0.032; p < 0.01) and food responsiveness (β = −0.09, ±0.030; p < 0.01). The results indicate that appetite may be a behavioural mediator of the well-established link between childhood deprivation and obesity risk.
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